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Yah216
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Arabic_poem_meter_classification

Text Classification
Transformers
PyTorch
Arabic
bert
Inference Endpoints
Model card Files Community
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Arabic_poem_meter_classification / README.md
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metadata
tags: autotrain
language: unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - Yah216/autotrain-data-poem_meter_classification
co2_eq_emissions: 1.8892280988467902

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 913229914
  • CO2 Emissions (in grams): 1.8892280988467902

Validation Metrics

  • Loss: 1.0592747926712036
  • Accuracy: 0.6535535147098981
  • Macro F1: 0.46508274468173677
  • Micro F1: 0.6535535147098981
  • Weighted F1: 0.6452975497424681
  • Macro Precision: 0.6288501119526966
  • Micro Precision: 0.6535535147098981
  • Weighted Precision: 0.6818087199275457
  • Macro Recall: 0.3910156950920188
  • Micro Recall: 0.6535535147098981
  • Weighted Recall: 0.6535535147098981

Usage

You can use cURL to access this model:

$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/Yah216/autotrain-poem_meter_classification-913229914

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Yah216/autotrain-poem_meter_classification-913229914", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Yah216/autotrain-poem_meter_classification-913229914", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)